qtum stock: Defiance Quantum & AI ETF Guide

QTUM (Defiance Quantum & AI ETF)

QTUM (Defiance Quantum & AI ETF) offers investors a thematic way to access companies exposed to quantum computing and machine learning. If you search for qtum stock to gain exposure to quantum and AI-related firms through an exchange-traded fund, this guide covers the ticker, index methodology, holdings, performance, risks, tax treatment, and how to invest — all in clear, beginner-friendly language.

Overview

QTUM is an exchange-traded fund listed on the Nasdaq that seeks to track the BlueStar Machine Learning & Quantum Computing Index. The ETF is issued by Defiance ETFs and targets companies with meaningful exposure to quantum computing and machine learning (AI) technologies. Investors using the qtum stock ticker are seeking thematic exposure to hardware, software, semiconductor, and service companies that contribute to or benefit from advances in quantum computing and AI.

Key Facts

This section summarizes the fund’s identifiers and basic facts. It is intended as a quick reference; always consult the prospectus and issuer materials for official, up-to-date details.

• Ticker: QTUM (commonly referenced when searching for qtum stock)
• Exchange: Nasdaq
• Inception date: September 4, 2018
• Structure: Open‑ended ETF
• Index tracked: BlueStar Machine Learning & Quantum Computing Index
• ISIN / CUSIP: Refer to the fund prospectus and issuer disclosures for the exact ISIN/CUSIP as reported by the issuer
• Expense ratio: commonly reported as 0.40%
• Assets under management (AUM): variable by reporting date; check the latest provider figures
• Share class: standard ETF share class as detailed in the prospectus

Investment Objective and Strategy

QTUM’s objective is to track the total return performance of the BlueStar Machine Learning & Quantum Computing Index before fees and expenses. The fund selects companies that have a measurable business exposure to quantum computing and/or machine learning technologies and weights them using a modified equal-weight approach that adjusts for liquidity and market-cap considerations.

The fund aims to provide diversified thematic exposure rather than betting on a single company or narrow subindustry. When investors search for qtum stock, they are typically seeking an ETF vehicle that aggregates many quantum- and AI-related exposures into one tradeable security.

Index Methodology

The BlueStar index applies a rules-based methodology to identify eligible companies. Key points of the methodology include:

• Eligibility: Companies that generate revenue from, develop, or provide products/services related to quantum computing, quantum materials, machine learning algorithms, AI software, AI infrastructure, and related semiconductors/hardware.
• Sector scope: Hardware, software, semiconductors, services, and materials are all considered if they have meaningful exposure to the themes.
• Screens: Liquidity and market-cap screens ensure constituents meet tradability thresholds; companies below thresholds are excluded or adjusted.
• Weighting: Usually a modified equal-weight or tiered equal-weight approach, which reduces concentration by limiting the largest names and increasing exposure to mid-size constituents, subject to liquidity constraints.
• Rebalancing: The index is rebalanced on a scheduled cadence (commonly semi-annual), with additional rules for corporate actions and eligibility changes.

These rules are intended to keep qtum stock exposures focused on companies materially tied to the quantum and AI themes while managing concentration and liquidity risks.

Holdings and Sector Exposure

QTUM typically holds about 80–81 individual securities, providing broad thematic coverage across related sub-sectors. The portfolio leans heavily toward technology but can also show meaningful exposure to industrials and communication services depending on constituent classification.

Typical features of the holdings include:

• Number of holdings: ~80–81 (varies slightly by reporting date)
• Sector concentration: High weighting to information technology, semiconductors, software, and select industrials
• Geographic exposure: Global, with a major weighting toward U.S. companies and developed-market firms, but also including select international names
• Representative holdings: Frequently reported examples across providers include well-known semiconductor and quantum/AI-related names such as AMD, IonQ, Rigetti, Micron, and other firms with relevant hardware or AI software exposure. These illustrative holdings are subject to change with periodic rebalances.

When evaluating qtum stock, investors should review the ETF’s latest holdings report to confirm current constituent weights and any recent changes.

Performance and Distributions

Performance metrics for QTUM are reported across multiple horizons by data providers (daily, 1‑month, 6‑month, year-to-date, 1-year, and multi-year returns). Performance and net asset value (NAV) fluctuate with market prices and the performance of constituent companies.

• Historical returns: As of Jan 24, 2026, according to Benzinga reporting, Defiance Quantum ETF (QTUM) showed material positive returns across recent periods (for example, Benzinga listed a one-year return figure in its ETF roundup). Always verify the latest performance on the issuer site or a reliable data provider.
• Distributions: The fund may distribute income; distribution frequency and characterization (ordinary dividends, qualified dividends, or return of capital) are outlined in the prospectus and reported in periodic distribution notices. Historically, QTUM has shown modest dividend yields (often in the lower single digits or under 1% in yield terms), but yield varies with market conditions.
• Expense impact: The expense ratio (commonly reported as 0.40%) reduces total returns over time compared to a zero-fee benchmark.

Note: Past performance is not indicative of future results. This article provides factual descriptions and does not constitute investment advice.

Trading and Market Data

QTUM trades on Nasdaq under the ticker QTUM and behaves like a listed security during market hours. Key trading considerations for those searching for qtum stock include:

• Intraday trading: QTUM can be bought or sold intraday at market prices that may trade at a premium or discount to NAV.
• Liquidity: Average daily volume and bid/ask spreads vary by date and market conditions; check real-time market data before trading.
• Market data reported: Price, NAV, AUM, 52-week range, and volume are commonly reported by financial data providers.

Because qtum stock trades like other ETFs, investors can use limit orders or market orders via their brokerage. For investors preferring a crypto-native platform or integrated asset services, consider using Bitget’s platform features where available for market research and account integration; consult Bitget for supported product listings and account services.

Tax Treatment and Distributions

For U.S. taxable investors, distributions from an ETF such as QTUM are typically treated as dividends and reported on Form 1099. The prospectus and annual tax information from the issuer will describe the character of distributions (ordinary income, qualified dividends, or capital gains).

Qualified dividend treatment depends on the underlying holding types and holding periods and is subject to tax code rules. Investors should consult the fund’s tax documents and a qualified tax professional to determine specific tax consequences for their situation.

Risks

QTUM, as a thematic ETF focused on quantum and AI-related companies, carries several principal risks investors should understand:

• Thematic/concentration risk: High exposure to a narrow, emerging technology theme can lead to greater volatility relative to broad-market funds.
• Technology and sector risk: Heavy weighting in technology and semiconductors may cause performance to diverge during tech cycles or industry-specific downturns.
• Company-specific risk: Individual holdings, especially smaller-cap or early-stage quantum firms, may be more volatile or subject to operational risk.
• Liquidity risk: Some constituents may trade less frequently, increasing bid/ask spreads and trading costs.
• Tracking error: Differences between the ETF’s performance and the index can arise due to fees, cash drag, and trading costs.

Given these risks, those researching qtum stock should weigh the thematic exposure against their portfolio objectives and risk tolerance and read the prospectus carefully.

Comparison and Related Funds

QTUM is one of several ETFs that target AI, semiconductors, or advanced computing themes. Comparable funds focus on AI, machine learning, semiconductors, or broader technology sectors. QTUM differentiates itself by explicitly targeting firms with exposure to quantum computing and machine learning via the BlueStar index and by using a modified equal-weight methodology. Expense ratios and index construction vary across similar products; compare methodology, fees, and holdings before deciding.

When you search qtum stock, consider how QTUM’s thematic focus and weighting approach align with your investment goals relative to broader tech or semiconductor ETFs.

History and Developments

• Inception: QTUM launched on September 4, 2018, to provide targeted exposure to quantum and machine learning areas.
• Methodology updates: Over time, index providers periodically refine eligibility rules or weighting schemes; consult the issuer for any documented changes.
• AUM and flows: Assets under management and investor flows have varied with market sentiment toward AI and quantum themes, including notable inflows during periods of strong AI sector performance reported by financial outlets.

As of Jan 24, 2026, Benzinga reported notable performance among AI- and tech-focused ETFs, and QTUM was among the ETFs highlighted for strong returns in recent periods. These market cycles can materially affect AUM and trading liquidity.

Reception and Coverage

Financial media and research platforms typically describe QTUM as a focused thematic ETF for investors seeking exposure to quantum computing and machine learning. Coverage often emphasizes the fund’s niche positioning and the speculative nature of some constituent firms.

• Media notes: As of Jan 24, 2026, Benzinga included Defiance Quantum ETF (QTUM) in a list of AI-linked ETFs, reporting strong trailing returns in a market environment where AI-related stocks drove notable performance across certain investor segments.
• Broader context: Analysts and commentators have linked surges in AI- and tech-related equities to concentrated gains among wealthier investors. For example, Moody’s Analytics Chief Economist Mark Zandi has discussed how speculative runs in tech and AI stocks contributed to widening consumption disparities in recent years. As reported in Moody’s analysis, these market-driven gains can amplify wealth effects for equity holders and influence broader economic patterns.

Readers searching for qtum stock should consult multiple reputable sources—issuer filings, fund fact sheets, and independent data providers—to form a fact-based view of the fund’s track record and exposures.

How to Invest

Practical steps for purchasing QTUM (the ticker often searched as qtum stock):

1. Research: Read the ETF prospectus, fund fact sheet, and the BlueStar index methodology to confirm the strategy, fees, distributions, and risks.
2. Brokerage account: Use a brokerage account that supports Nasdaq-listed ETFs. If you prefer an integrated crypto and asset platform for research and account features, consider Bitget for available tools and wallet integration; verify product availability for your jurisdiction.
3. Order types: Place market or limit orders; consider liquidity and spread when entering larger trades.
4. Monitor: Track holdings reports, NAV vs. market price behavior, rebalancing dates, and distribution notices.

This article is informational and not investment advice. Investors should conduct their own due diligence and consult a financial professional regarding suitability.

Governance and Provider

Defiance ETFs is the issuer of QTUM, serving the role of sponsor and primary distributor for its ETF suite. The fund operates under a trust structure and follows governance and regulatory requirements for U.S.-listed ETFs. Fund governance details, including adviser names, board composition, and service providers, are disclosed in the prospectus and annual reports.

If you are researching qtum stock, review the issuer’s governance disclosures and any stated index licensing arrangements with BlueStar for added transparency.

References and External Links

Primary sources to consult when researching QTUM include the fund prospectus, the Defiance ETFs issuer webpage, and the BlueStar index methodology documents. Data providers such as Yahoo Finance, TradingView, Morningstar, and Benzinga publish up-to-date market data and performance metrics. For tax or legal questions, consult the fund’s official tax documents and a qualified advisor.

As of Jan 24, 2026, according to Benzinga reporting, QTUM was highlighted among AI-related ETFs for strong recent performance; always verify figures on official issuer pages or regulatory filings.

Appendix: Disambiguation — Qtum (cryptocurrency)

Note: The term "Qtum" also refers to a blockchain platform and native cryptocurrency token that is unrelated to the Defiance Quantum & AI ETF (ticker QTUM). The cryptocurrency Qtum is a separate protocol focused on smart contracts and decentralized applications and should be covered in its own, dedicated article focusing on tokenomics, protocol design, and ecosystem developments.

Further exploration: If you want to compare qtum stock with other AI- and semiconductor-focused ETFs, consult fund fact sheets and data providers, and consider using Bitget’s research features and Bitget Wallet for portfolio tracking where supported.